吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (增刊1): 173-178.

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Agent-based evolutionary approach towards solving constrained multi-objective optimization problems

DING Hui, LI Hong-guang   

  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2011-02-14 Online:2011-09-01 Published:2011-09-01

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Abstract:

In regard to constrained multi-objective optimization problems which are traditionally intractable by means of agent based evolutionary algorithm,the normalized violation degrees of the constraints were considered as additional objectives able to influence the energy of the agents.Additionally,two external archives,an optimal solution set and an optimal feasible solution set were available to maintain the diversity of population.It is efficient to achieve the optimal solutions by carrying out climbing operations on both candidate solutions and agents with small violation degrees.Case studies consisting in test functions and optimal design of welded beams show that the proposed algorithm not only keep the diversity of population but also converge to the optimal fronts quickly.

Key words: artificial intelligence, evolutionary algorithm, constrained multi-objective optimization, agents

CLC Number: 

  • TP3


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